美国医疗保健 AI 市场：服务细分和最终用户的分析和预测（2024-2034 年）

美国医疗保健 AI 市场规模预计将从 2023 年的 52.543 亿美元增长到 2034 年的 2,2969.94 亿美元，预测期内复合年增长率高达 40.41%。

这一令人印象深刻的成长是由快速的技术进步所推动的，这些技术从根本上重塑了医疗保健服务。机器学习和深度学习演算法的突破性进展正在推动高精度诊断工具和个人化治疗方案的发展，从而改善患者的治疗效果和业务效率。穿戴式装置和远端医疗等数位健康解决方案的整合将进一步扩展人工智慧的功能，实现即时监控和远端病患管理。来自私人和公共部门的大量投资正在加速研究和开发，促进创新和应用的持续循环。此外，支援性的监管环境和行业相关利益者之间的策略伙伴关係为在传统医疗保健框架内无缝采用人工智慧解决方案铺平了道路，促进了知识交流和技术整合。这些因素将支持未来十年美国医疗保健人工智慧市场的快速成长并创造强大的生态系统。

在产品供应方面，软体和服务业处于领先地位：

根据产品细分，软体和服务细分市场将在 2023 年以 72% 的份额引领市场。我们的软体和服务提供全面的解决方案，包括预测分析和辅助诊断到电子健康记录整合和自然语言处理，帮助医疗保健提供者提高临床决策和业务效率。这些工具可实现即时资料处理和个人化治疗计划，最终有助于改善患者的治疗效果并显着节省成本。就像先进的作业系统可以无缝整合不同的应用程式以优化效能一样，这些软体主导的解决方案是医疗保健数位转型的支柱，简化了工作流程并促进更快、更准确的诊断。随着对数位健康创新的持续投入，软体和服务的重要性预计将继续增长，并在塑造更有效率、以患者为中心的医疗保健环境中发挥关键作用。

按最终用户划分，其他医疗保健提供者细分市场占主导地位：

根据最终用户，其他医疗保健提供者部门在 2023 年占据 46% 的市场份额，占据市场主导地位。其他医疗保健提供者包括专科诊断中心、门诊诊所、门诊护理中心和独立实验室。这些营业单位越来越多地采用人工智慧主导的测试解决方案来提高诊断准确性，减少週转时间，并客製化治疗通讯协定以获得更好的患者结果。透过利用先进的演算法和即时资料分析，我们可以识别传统测试方法可能忽略的模式和异常。就像互联医疗保健系统中的专家网络一样，这些提供者在扩大尖端诊断技术的使用范围、推动医疗保健的数位转型以及最终有助于提供更高效、个性化的医疗服务方面发挥关键作用。

市场区隔

细分一：按产品

• 硬体
• 软体与服务

细分 2：按最终用户

• 医疗保健提供者
• 医疗支付者
• 病人
• 其他医疗保健提供者

本报告研究了美国医疗保健AI市场，并总结了主要趋势、影响市场的因素分析、法律制度、技术发展和专利趋势、案例研究、市场规模趋势和预测、各个细分市场的详细分析、竞争格局以及主要企业的概况。

目录

执行摘要

范围和定义

第一章市场：产业展望

• 市场概况
  • 医疗人工智慧简介
  • 医疗保健人工智慧的用案例
  • 人工智慧所使用的技术
• 市场趋势和采用率
  • 扩大数位技术的采用
  • 扩大资金筹措力度
  • 医疗人工智慧的新应用
• 人工智慧的采用和市场准备
• 进入障碍和机会
• 案例研究和影响
• 监管状态
• 市场动态概览
  • 影响分析
  • 市场驱动因素
  • 市场挑战
  • 市场机会

第 2 章：美国医疗保健 AI 市场（按服务细分）

• 硬体
• 软体与服务

第 3美国。

• 医疗保健提供者
• 医疗支付者
• 病人
• 其他医疗保健提供者

第 4 章市场：竞争基准化分析与公司简介

• 关键策略和发展
• 投资格局（资金筹措和併购活动）
• 主要 AI 产品和Start-Ups
  • Viz.ai
  • Abridge
  • Insilico Medicine
  • Tempus
• 公司简介
  • International Business Machines Corporation
  • Google LLC
  • Microsoft Corporation
  • Amazon.com, Inc.
  • NVIDIA Corporation
  • GE HealthCare
  • Koninklijke Philips NV
  • Tempus Labs, Inc.
  • PathAI

第五章调查方法

Introduction of U.S. AI in Healthcare Market

The U.S. AI in healthcare market, initially valued at $5,254.3 million in 2023, is set for substantial growth, projected to surge to $229,699.4 million by 2034, marking a remarkable compound annual growth rate (CAGR) of 40.41% over the period from 2024 to 2034. This impressive trajectory is fuelled by rapid technological advancements that are fundamentally reshaping healthcare delivery. Breakthroughs in machine learning and deep learning algorithms drive the development of highly accurate diagnostic tools and personalized treatment plans, improving patient outcomes and operational efficiencies. The integration of digital health solutions, such as wearable devices and telemedicine, further expands the capabilities of AI, enabling real-time monitoring and remote patient management. Significant investments from both private and public sectors are accelerating research and development, fostering a continuous cycle of innovation and application. Additionally, a supportive regulatory environment is paving the way for seamless adoption of AI solutions within traditional healthcare frameworks, while strategic partnerships among industry stakeholders are facilitating knowledge exchange and technological integration. Together, these factors create a robust ecosystem that not only supports but actively propels the rapid growth of the U.S. AI in healthcare market over the coming decade.

Market Introduction

The AI in healthcare market in the U.S. has been experiencing significant growth, driven by rapid technological innovation, evolving regulatory support, and a surge in strategic investments. Advanced AI applications, including predictive analytics and sophisticated diagnostic tools, are transforming traditional healthcare practices by enabling more accurate and timely clinical decision-making. This shift is further bolstered by the integration of digital health solutions, such as wearable devices and telemedicine, which facilitate continuous patient monitoring and remote care. Additionally, healthcare providers are increasingly embracing data-driven approaches to enhance personalized treatment protocols and improve overall patient outcomes. As these technological advancements align with a broader move towards preventive care and operational efficiency, the U.S. AI in healthcare market is witnessing a paradigm shift reshaping healthcare delivery's future.

Industrial Impact

The U.S. AI in healthcare market is set for steady growth, driven by rapid technological advancements, supportive regulatory frameworks, and increased investments in digital health innovation. Emerging AI algorithms and machine learning platforms are enhancing diagnostic accuracy and enabling personalized treatment plans, while streamlined government initiatives and evolving FDA guidelines are creating an environment conducive to integrating AI into clinical practices.

The industrial impact of AI in healthcare is profound, fundamentally reshaping clinical processes and operational efficiencies across the sector. AI-driven solutions have been shown to reduce diagnostic errors by up to 30%, leading to more accurate treatments and significant cost savings, bolstering the $500 million in venture capital funding secured by U.S.-based healthcare AI startups in 2023. This influx of investment is accelerating innovation, paving the way for advanced diagnostic tools and predictive analytics that are streamlining workflows in hospitals and clinics alike. Moreover, governmental initiatives, including those by the U.S. Department of Health and Human Services, project up to $150 billion in annual savings by 2026 through optimized treatment protocols and reduced misdiagnoses. These factors collectively are not only enhancing patient outcomes but are also transforming healthcare institutions into agile, data-driven entities, much like a well-orchestrated industrial upgrade that replaces outdated systems with next-generation technologies, thereby setting new benchmarks for efficiency and quality in healthcare delivery.

Market Segmentation:

Segmentation 1: by Offering

• Hardware
• Software and Services

Software and Services Offering Segment to Dominate the U.S. AI in Healthcare Market (by Offering)

Based on offering, the U.S. AI in healthcare market was led by the software and services offering segment, which held a 72% share in 2023. Software and services offer a comprehensive suite of solutions, ranging from predictive analytics and diagnostic support to electronic health record integration and natural language processing, that empower healthcare providers to enhance clinical decision-making and operational efficiency. These tools enable real-time data processing and personalized treatment planning, ultimately contributing to improved patient outcomes and significant cost savings. Much like an advanced operating system that seamlessly integrates various applications to optimize performance, these software-driven solutions serve as the backbone of digital transformation in healthcare, streamlining workflows and facilitating faster, more accurate diagnoses. With ongoing investments in digital health innovation, the prominence of software and services is expected to continue expanding, solidifying its pivotal role in shaping a more efficient and patient-centric healthcare landscape.

Segmentation 2: by End User

• Healthcare Providers
• Healthcare Payers
• Patients
• Other Healthcare Providers

Other Healthcare Providers Segment to Dominate the U.S. AI in Healthcare Market (by End User)

Based on the end user, the U.S. AI in healthcare market was led by the other healthcare providers segment, which held a 46% share in 2023. Other healthcare providers are a diverse group that includes specialized diagnostic centers, outpatient clinics, ambulatory care centers, and independent laboratories. These entities are increasingly adopting AI-driven testing solutions to enhance diagnostic accuracy, reduce turnaround times, and tailor treatment protocols for better patient outcomes. By leveraging advanced algorithms and real-time data analytics, they are able to identify patterns and anomalies that might otherwise be overlooked in traditional testing methods. Much like a network of interconnected specialists in a well-coordinated healthcare system, these providers play a crucial role in expanding access to cutting-edge diagnostic technologies, driving the digital transformation of healthcare, and ultimately contributing to more efficient and personalized care delivery.

Recent Developments in the U.S. AI in Healthcare Market

• In October 2023, Medtronic Plc partnered with Nvidia to build an AI platform for medical devices.
• In July 2022, Amazon.com, Inc. acquired One Medical for $3.9 billion, expanding AI-enabled primary care.

Demand - Drivers, Challenges, and Opportunities

Market Drivers:

Growing Need for Early Detection and Diagnosis: The growing need for early detection and diagnosis has become increasingly critical as the complexity of healthcare challenges continues to rise. Timely identification of diseases allows for prompt and targeted intervention, which can significantly enhance treatment effectiveness. Innovative diagnostic technologies, particularly AI-powered, enable clinicians to detect subtle changes and early warning signs that might otherwise go unnoticed. Early diagnosis paves the way for personalized care plans and reduces the risk of severe complications. By shifting the focus toward prevention rather than reaction, healthcare systems are better equipped to manage patient outcomes proactively. This proactive approach alleviates long-term burdens on healthcare resources and minimizes overall treatment costs. Ultimately, the emphasis on early detection is driving a transformative shift toward precision medicine and a more sustainable future for patient care.

Market Challenges:

Concerns Regarding Data Privacy: Data privacy concerns in healthcare have become increasingly significant as AI systems process vast amounts of sensitive patient information. The aggregation of data from diverse sources introduces vulnerabilities that can lead to unauthorized access and data breaches, putting personal health records at risk. Regulatory frameworks, although robust, often struggle to keep pace with rapid technological advancements and the complexities of cross-border data flows. This situation underscores the challenge of balancing the benefits of AI-driven healthcare innovations with the imperative to protect patient confidentiality. Healthcare organizations are, therefore, investing heavily in cybersecurity measures, such as advanced encryption and data anonymization, to mitigate these risks. At the same time, ongoing updates to privacy regulations and best practices are essential to address evolving cyber threats. Ultimately, maintaining stringent data protection protocols is critical to preserving patient trust and ensuring the ethical use of AI in healthcare.

Market Opportunities:

Pain Management and Personalized Care: AI-driven innovations are revolutionizing pain management by offering highly personalized care tailored to each patient's unique needs. Continuous monitoring through wearable devices and sensors captures real-time data on pain levels, enabling clinicians to adjust treatments promptly and effectively. Advanced data analytics identify individual pain triggers and patterns, paving the way for targeted and efficient interventions. Enhanced diagnostic imaging further refines these approaches by accurately pinpointing the sources of pain, which supports the development of more precise treatment strategies. Integration with telemedicine platforms also plays a crucial role, allowing remote monitoring and timely consultations that ensure care remains responsive and accessible. By combining historical patient data with live insights, clinicians can create dynamic pain management plans that evolve with each patient's condition. Ultimately, this personalized approach improves pain control and enhances overall quality of life, empowering patients through tailored, proactive care.

How can this report add value to an organization?

Product/Innovation Strategy: The U.S. AI in healthcare market has been extensively segmented based on various categories, such as offerings and end users. This can help readers understand which segments account for the largest share and which are well-positioned to grow in the coming years.

Growth/Marketing Strategy: Mergers, acquisitions, and product launches accounted for the maximum number of key developments, i.e., nearly 41.67% of the total developments in the U.S. AI in healthcare market were between January 2019 and December 2023.

Competitive Strategy: The U.S. AI in healthcare market has numerous established players with product portfolios. Key players in the U.S. AI in healthcare market analyzed and profiled in the study involve established players offering products for U.S. AI in healthcare.

Methodology

Key Considerations and Assumptions in U.S. AI in Healthcare Market Engineering and Validation

• The base year considered for the calculation of the U.S. AI in healthcare market size is 2023. A historical year analysis has been done for the period FY2021-FY2022. The U.S. AI in healthcare market size has been estimated for FY2023 and projected for the period FY2024-FY2034.
• The scope of this report has been carefully derived based on interactions with experts in different companies. This report provides a market study of upstream and downstream technologies of the U.S. AI in healthcare market.
• The U.S. AI in healthcare market contribution of U.S. AI in healthcare is anticipated to be launched and calculated based on a historical analysis of the solutions.
• The company's revenue has been referenced from their annual reports for FY2022 and FY2023. For private companies, revenues have been estimated based on factors such as inputs obtained from primary research, funding history, market collaborations, and operational history.
• The U.S. AI in healthcare market has been mapped based on the available U.S. AI in healthcare data. This report has considered and profiled all the key companies with significant offerings in this field.

Primary Research:

The primary sources involve industry experts in U.S. AI in healthcare, including the market players offering products and services. Resources such as CEOs, vice presidents, marketing directors, and technology and innovation directors have been interviewed to obtain and verify both qualitative and quantitative aspects of this research study.

The key data points taken from the primary sources include:

• Validation and triangulation of all the numbers and graphs
• Validation of the report's segmentation and key qualitative findings
• Understanding the competitive landscape and business model
• Current and proposed production values of a product by market players
• Validation of the numbers of the different segments of the U.S. AI in healthcare market in focus
• Percentage split of individual markets for regional analysis

Secondary Research

Open Sources

• Certified publications, articles from recognized authors, white papers, directories, and major databases, among others
• Annual reports, SEC filings, and investor presentations of the leading market players
• Company websites and detailed study of their product portfolio
• Gold standard magazines, journals, white papers, press releases, and news articles
• Paid databases

The key data points taken from the secondary sources include:

• Segmentations and percentage shares
• Data for market value
• Key industry trends of the top players of the U.S. AI in healthcare market
• Qualitative insights into various aspects of the U.S. AI in healthcare market, key trends, and emerging areas of innovation
• Quantitative data for mathematical and statistical calculations

Key Market Players and Competition Synopsis

Profiled companies have been selected based on inputs gathered from primary experts, who have analysed company coverage, product portfolio, and market penetration.

Some prominent names established in this market are:

• International Business Machines Corporation
• Google LLC
• Microsoft Corporation
• Amazon.com, Inc.
• NVIDIA Corporation
• GE HealthCare

Table of Contents

Executive Summary

Scope and Definition

1 Market: Industry Outlook

• 1.1 Market Overview
  • 1.1.1 AI Adoption in Healthcare
  • 1.1.2 AI Use Cases in Healthcare
    • 1.1.2.1 Diagnostics and Imaging
    • 1.1.2.2 Drug Discovery and Development
    • 1.1.2.3 Personalized Medicine and Treatment Plans
    • 1.1.2.4 AI in Patient Management and Virtual Healthcare
    • 1.1.2.5 Remote Patient Monitoring (RPM)
    • 1.1.2.6 Hospital Operations and Administrative Automation
    • 1.1.2.7 AI in Surgery and Robotics
    • 1.1.2.8 AI for Disease Prediction and Early Detection
  • 1.1.3 Technology Used in AI
    • 1.1.3.1 Machine Learning
    • 1.1.3.2 Natural Language Processing (NLP)
    • 1.1.3.3 Generative AI
    • 1.1.3.4 Computer Vision
    • 1.1.3.5 Image Analysis
• 1.2 Market Trends and Adoption Rates
  • 1.2.1 Increasing Adoption of Digital Technology
  • 1.2.2 Increasing Funding Initiatives
  • 1.2.3 Emerging Applications of AI in Healthcare
• 1.3 AI Adoption vs Market Readiness
• 1.4 Entry Barriers and Opportunities
  • 1.4.1 Barriers
    • 1.4.1.1 Regulatory Uncertainty
    • 1.4.1.2 Integration Complexity
    • 1.4.1.3 Workforce Transition
    • 1.4.1.4 Data Strategy
    • 1.4.1.5 ROI Realization
  • 1.4.2 Opportunities
    • 1.4.2.1 Strategic Differentiation
    • 1.4.2.2 New Services and Revenue Streams
    • 1.4.2.3 Addressing Workforce Shortages
    • 1.4.2.4 Collaboration and Ecosystem Building
• 1.5 Case Studies and Impact
  • 1.5.1 Stroke Care (Viz.ai)
  • 1.5.2 Sepsis Early Detection-Mixed Results
  • 1.5.3 Diagnostic Accuracy
  • 1.5.4 Patient Satisfaction-AI Patient Communication
  • 1.5.5 Telehealth Triage-Kaiser's Chatbot
• 1.6 Regulatory Landscape
  • 1.6.1 Regulatory and Policy Landscape in the U.S.
  • 1.6.2 EU vs. U.S. Differences
• 1.7 Market Dynamics Overview
  • 1.7.1 Impact Analysis
  • 1.7.2 Market Drivers
    • 1.7.2.1 Growing Need for Early Detection and Diagnosis
    • 1.7.2.2 The Rapid Proliferation of AI in the Healthcare Sector
    • 1.7.2.3 Exponential Growth in Data Volume and Complexity Due to Surging Adoption of Digital Technologies
    • 1.7.2.4 Operational Efficiency and Cost Reduction
  • 1.7.3 Market Challenges
    • 1.7.3.1 Concerns Regarding Data Privacy
  • 1.7.4 Market Opportunities
    • 1.7.4.1 Pain Management and Personalized Care

2 U.S. AI in Healthcare Market (by Offering), $Billion, 2023-2034

• 2.1 Hardware
• 2.2 Software and Services

3 U.S. AI in Healthcare Market (by End User), $Billion, 2023-2034

• 3.1 Healthcare Providers
• 3.2 Healthcare Payers
• 3.3 Patients
• 3.4 Other Healthcare Providers

4 Markets - Competitive Benchmarking & Company Profiles

• 4.1 Key Strategies and Development
  • 4.1.1 Partnerships, Alliances, and Business Expansions
  • 4.1.2 Funding Activities
  • 4.1.3 Merger and Acquisition
  • 4.1.4 New Offerings and Regulatory Approval
• 4.2 Investment Landscape (Funding and M&A Activity)
• 4.3 Major AI Products and Startups (2023-2025)
  • 4.3.1 Viz.ai
  • 4.3.2 Abridge
  • 4.3.3 Insilico Medicine
  • 4.3.4 Tempus
• 4.4 Company Profiles
  • 4.4.1 International Business Machines Corporation
    • 4.4.1.1 Overview
    • 4.4.1.2 Top Products/Services
    • 4.4.1.3 Top Competitors
    • 4.4.1.4 Target Customers
    • 4.4.1.5 Analyst View
  • 4.4.2 Google LLC
    • 4.4.2.1 Overview
    • 4.4.2.2 Top Products/Services
    • 4.4.2.3 Top Competitors
    • 4.4.2.4 Target Customers
    • 4.4.2.5 Analyst View
  • 4.4.3 Microsoft Corporation
    • 4.4.3.1 Overview
    • 4.4.3.2 Top Products/ Services
    • 4.4.3.3 Top Competitors
    • 4.4.3.4 Target Customers
    • 4.4.3.5 Analyst View
  • 4.4.4 Amazon.com, Inc.
    • 4.4.4.1 Overview
    • 4.4.4.2 Top Products/ Services
    • 4.4.4.3 Top Competitors
    • 4.4.4.4 Target Customers
    • 4.4.4.5 Analyst View
  • 4.4.5 NVIDIA Corporation
    • 4.4.5.1 Overview
    • 4.4.5.2 Top Products/ Services
    • 4.4.5.3 Top Competitors
    • 4.4.5.4 Target Customers
    • 4.4.5.5 Analyst View
  • 4.4.6 GE HealthCare
    • 4.4.6.1 Overview
    • 4.4.6.2 Top Products/ Services
    • 4.4.6.3 Top Competitors
    • 4.4.6.4 Target Customers
    • 4.4.6.5 Analyst View
  • 4.4.7 Koninklijke Philips N.V.
    • 4.4.7.1 Overview
    • 4.4.7.2 Top Products/ Services
    • 4.4.7.3 Top Competitors
    • 4.4.7.4 Target Customers
    • 4.4.7.5 Analyst View
  • 4.4.8 Tempus Labs, Inc.
    • 4.4.8.1 Overview
    • 4.4.8.2 Top Products/ Services
    • 4.4.8.3 Top Competitors
    • 4.4.8.4 Target Customers
    • 4.4.8.5 Analyst View
  • 4.4.9 PathAI
    • 4.4.9.1 Overview
    • 4.4.9.2 Top Products/Services
    • 4.4.9.3 Top Competitors
    • 4.4.9.4 Target Customers
    • 4.4.9.5 Analyst View

5 Research Methodology

• 5.1 Data Sources
  • 5.1.1 Primary Data Sources
  • 5.1.2 Secondary Data Sources
  • 5.1.3 Data Triangulation
• 5.2 Market Estimation and Forecast

List of Figures

• Figure 1: U.S. AI in healthcare Market (by Offering), $Billion, 2023 and 2034
• Figure 2: U.S. AI in healthcare Market (by End User), $Billion, 2023 and 2034
• Figure 3: Key Events to Keep Track of in the U.S. AI in Healthcare Market
• Figure 4: AI Adoption Vs. Market Readiness Across Healthcare Applications
• Figure 5: Share of Strategic Initiatives, January 2019-December 2023
• Figure 6: Strategic Initiatives (by Year), January 2019-December 2023
• Figure 7: Partnerships, Alliances, and Business Expansions, January 2019-December 2023
• Figure 8: Funding Activities, January 2019-December 2023
• Figure 9: Merger and Acquisition, January 2019-December 2023
• Figure 10: New Offerings and Regulatory Approval, January 2019-December 2023
• Figure 11: Data Triangulation
• Figure 12: Top-Down and Bottom-Up Approach
• Figure 13: Assumptions and Limitations

List of Tables

• Table 1: Market Snapshot
• Table 2: Impact Analysis of U.S. AI in Healthcare Market Navigating Factors, 2024-2034
• Table 3: U.S. AI in Healthcare Market (by Offering), $Billion, 2023-2034
• Table 4: U.S. AI in Healthcare Market (by End User), $Billion, 2023-2034